A Shared Socio-economic Pathway Approach to Assessing the Future of the New Zealand Forest Sector

Adam Daigneault, University of Maine School of Forest Resources

Anne-GaelleAusseil, Landcare Research New Zealand

MikoKirschbaum, Landcare Research New Zealand

Overview

This analysis focuses on impacts of climate and socio-economic change through 2100 on the New Zealand forest sector. The industry is based around sustainably managed exotic plantation forests, covering 1.8 million hectares, or 7% of New Zealand's land area. About 90% of plantations are Radiata pine (Pinusradiata), with Douglas-fir and eucalypts largely accounting for the remaining area. Although New Zealand is a small player in the global forestry industry, contributing just over 1% of the world's total industrial wood supply, it a significant industry in New Zealand. Economy-wise, the sector accounts for 3% of New Zealand's GDP and wood products are New Zealand's third largest export, behind dairy and meat (MPI, 2016). Furthermore, 30% of the country is covered in forest which sequesters about 20 million tons of carbon dioxide equivalent, (MtCO-e/yr), thus reducing the country’s total GHG emissions by about 1/3 (MfE, 2016a). New Zealand also has some of the highest erosion rates in the world, and sediment loads in many areas are largely mitigated by its extensive forest cover (Dymond et al 2010).

We use a global integrated assessment model that is focused on the land use sector to model 20 different scenarios that vary climate and socio-economic pathwaysto analyze the potential impacts on the New Zealand forest sector. The dynamic model includes a global computable CGE model, a global timber supply model, and a detailed New Zealand land-use sector model that utilizes agriculture and forest production models that estimate forest, pasture, and livestock yields under varying climatic conditions. Key outputs include land use area, forest carbon sequestration, timber harvest, and management regime. This study provides insight on the key drivers that are most likely to affect New Zealand’s forest sector, including population change,commodity prices, agricultural yields, and pricing land-based GHG emissions. It also offers valuable insight on possible methods to utilize ‘downscaled’ global climate projections and region-specific socio-economic assumptions into national and sub-national scale integrated assessments.

Methodology

We take a scenario modelling approach that adopts two global elements from a scenario toolkit (Ebi et al., 2013) to estimate a wide range of possible changes to the New Zealand and global forest market as a result of climate and socio-economic change. The scenarios we analyze follow the framework by van Vuuren and Carter (2013) to illustrate combinations of Representative Concentration Pathways (RCPs) and Shared Socioeconomic Pathways (SSPs). We then describe potential climate change mitigation and/or adaptation options specific to New Zealand to weave the RCP and SSPs together using methods similar to Riahi et al. (2016). A combination of four RCPs (2.6, 4.5 6.0 and 8.5 W/m2) and five SSPs (1-5) were run through a dynamic integrated assessment model using a mix of exogenous input assumptions and endogenous model responses to assess and the potential outcome of 20 distinct scenarios.

The New Zealand climate change projections for are based on four RCPs modelled via the Coupled Model Inter-comparison Project (CMIP5) ofnumerous Earth System Models or General Circulation Models (GCM). We use dynamic downscaled estimates from six GCMs to update and improve regional-scale projections of New Zealand climate trends and variability to 2100 (MfE 2016b). The key output variables are precipitation, maximum and minimumair temperature, relative humidity, vapor pressure, solar radiation, and wind speed. Each variable wasestimatedfor New Zealand on a regular grid (0.05°, approximately 5km) at a daily, monthly and annual temporal resolution for the 1971–2100 periodand bias-corrected relative to a 1986–2005 climatology (Tait and Turner 2005).

For scenario modelling, we used the New Zealand Integrated Assessment Modelling System (NZIAMS) to estimate impacts of climate and socio-economic change through 2100 on the global forests, with a detailed focus on New Zealand land use (Lennox et al., 2013). The integrated approach links (a) the Climate and Trade Dynamic General Equilibrium (CliMAT-DGE) (Fernandez and Daigneault 2015),(b) the Global Timber Model (GTM), (Tian et al 2016) and (c) the New Zealand Forest and Agriculture Regional Model (NZFARM) (Daigneault et al. 2017) to form a multi-regional, multi-sectoral, dynamic optimization model. While the CGE component of the model can track all major sectors of the global economy, NZIAMS has been parameterized to focus particularly on the forest and agriculture sectors, where the objective is to maximize net farm revenue subject to a range of input and land use change constraints.

Climate impacts on the NZ forest sector are modelled at the 5km grid scale level using the process-based ecophysiologicalforest productivity model, CenW (Kirschbaum and Watt 2011), that was recently updated to account for the downscaled CMIP5 climate projections. In addition to the effect of standard model parameters such as temperature and precipitation, we estimate the possible impacts of climate change on NZ forests under constant and increasing CO2. Similar approaches were also used to estimate climate change impacts on agricultural crops (Holzworth et al. 2014) and pasture (Keller et al. 2014) yields to ensure that all major land uses are accounted for.

The productivity estimates from the agriculture and forestry yield modelsserve as input into the NZIAMS land use models along with global(e.g, population & GDP growth) and national (e.g., land management preferences) level SSP assumptions to establish the key global and NZ-drivers that can have an effect on commodity prices, GHG prices, and resulting land use and forest management. For these scenarios, we assumed that forest Figure 1 illustrates the key components of NZIAMS and how they are integrated.

Preliminary Results

Forest productivity estimates across the RCP-only scenarios (i.e. only climate change impacts) varied most by assumption about whether plants respond to changes in CO2. As expected, results varied by RCP and GCM, with the greatest impacts occurring under the RCP 8.5. For simulations with constant CO2, we estimate a 0-8% decline in NZ forest plantation productivity relative to today by 2100. For simulations with increasing CO2, growth increased by about 10-40%. Scenarios that also accounted for SSP-related assumptions and thus socio-economic impacts in addition to climate change produced a wide range of results. In general, scenarios including RCP 8.5 resulted in relatively small change in NZ’s forest area, timber production, and carbon sequestration due to the lack of an environmental drivers such as a carbon price to influence landowners to afforest their land. The RCP 8.5/SSP 3 scenario resulted in the largest decline for the forest sector, which is consistent with recent global analyses (e.g. Popp et al. 2016). On the other extreme, RCP 2.6 estimated that a global GHG prices of $500/tCO2-e or more by 2100 were required to meet the emissions reduction targets, regardless of the SSP assumptions. The effect of placing a price on all sectors of the economy, including crops and livestock, dominated all other drivers, resulting in forest area and related outputs in NZ nearly doubling. In addition, the large increase in forest carbon sequestration coupled with the decline in emissions from other sectors is likely to make the country a net GHG sink by the end of the century. More details and insight on these and other findings will be provided in the full paper and presentation.

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